Breaking down the AI trust barrier: turning doubt into opportunity

Gong, a revenue AI company, has published research highlighting a trust-related barrier affecting AI adoption in organisations. The study, supported by Gong Labs, found that 58% of companies have experienced delays in AI projects. The report attributes this primarily to concerns around trust rather than budget constraints.

Key areas cited include data privacy, security, and transparency, which are linked to slower adoption rates. Based on aggregated and de-identified data from more than 25 million sales interactions, Gong Labs identified security and underlying AI data mechanisms as topics referenced in approximately one in four calls.

Additional research involving over 2,000 business leaders in the US and UK found that transparency in AI outputs is considered important for adoption. The study notes that 75% of leaders believe their organisations are behind in realising AI’s potential.

The report identifies several factors that can affect confidence in AI tools, including:

• Data privacy and security
• Explainability
• Model transparency
• Regulatory uncertainty

More than half of organisations surveyed reported delaying or cancelling AI adoption plans, with around 46% of planned AI investments reported as paused.

The findings suggest that certain assurances may influence adoption decisions, including:

• Explainability of AI outputs
• Defined model guardrails for data protection
• Security assurances within solutions
• Third-party audits or certifications
• Transparency in how training data is used
• Transparent model logic

Gong states that it aims to address these concerns by incorporating security and data governance features into its Revenue AI Operating System, designed to generate context-based insights from aggregated usage patterns. The platform also includes redaction capabilities intended to support use in regulated environments, allowing organisations to analyse data while managing privacy constraints.